MIMO Semi-blind Channel Estimation by using Tikhonov Regularized MMSE and MAP Algorithms with Householder Transformation based QR Decomposition

Payal Saxena, Sagarkumar Patel, Jaymin Bhalani

In this paper, we present novel semi-blind channel estimation schemes for Rayleigh fading Multi-Input Multi-Output (MIMO) channel. Here channel matrix H is decomposed as an upper triangular matrix R, which can be estimated blindly using the Householder transformation based QR decomposition of received output covariance matrix and Q matrix, which can be estimated using the Tikhonov regularization-based MAP (maximum a posteriori) and MMSE (minimum mean square error) techniques with the help of singular value decomposed orthogonal pilot symbols. Simulation results in terms of BER performance obtained for BPSK and 4-PSK data modulation schemes using Alamouti coded 2×6 (2 transmitter and 6 receiver antennas) and 2×8 (2 transmitter and 8 receiver antennas) cases by choosing different values of regularization parameter λ. Appropriate choice of regularization parameter can be calculated using discrepancy principles that gives better performance in terms of BER. The paper proposes the novel semi-blind channel estimation approach using the Householder QR decomposition based blind estimation of R and Tikhonov regularized based MMSE and MAP algorithms using pilot symbols for estimation of Q will yield good results in channel estimation methods.